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Data augmentation occurs when adding additional training examples by transforming existing examples.

This is further explained below.

What is Data augmentation?

Generally, The technique of producing additional data points from previously collected data is known as data augmentation.

This procedure is used to artificially increase the quantity of data that is collected.

This may include making insignificant adjustments to the data or employing machine learning algorithms in order to produce additional data points inside the latent space of the original data in order to magnify the dataset.

In conclusion, Data augmentation is the process of adding more training instances by changing the examples that are already there.

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